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I do have a bit of experience with LLM locally, to test the limits of what it can do consistently. 16000 token context windows don't seem like enough to me to tackle this task. I don't know that it's possible to distill my musical tastes into a small enough number of tokens, for instance. Nevermind that you need humans to review the music, currently; unless there's magical song tagging models out there i haven't heard of.

there are minimally invasive mechanisms, like kongregate and that .io game site use, "people also played ..."; most aggregators suck, though. Netflix has always recommended stuff ("For you" or whatever) that i have no interest in, amazon recommends things that i would never buy - or have already bought, including from amazon. Pandora was awesome before everyone uploaded every song to youtube, now it's just a collection of playlists that play the same 20 songs over and over each time you start it.

I don't use and haven't used spotify or any other "music" service, because of pandora experiences and youtube. Also in my car i prefer to listen to old time radio which is easily discoverable* enough for at least a few years of content. Just copy to a USB stick and plug into the car. And my big issue with podcasts is i don't enjoy listening to most (nearly all) people just "talking", especially if they're chewing the scenery to make it more of a "captivating" experience.

I do miss mp3 streaming sites, though. My favorite one went dark during the pandemic, is still dark, and shoutcast dot com has sucked for discovery for at least half a decade if not longer. I think it's mostly popular in non-english speaking countries these days, at a glance.

* OTRR - old time radio researchers, there's otrrpedia and an online player available, the content itself lives on archive.org - i have about a TB of radioplays/content from there that i rotate through (only) in the car.




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